Exercise-Based Entertainment And Game Controller To Improve Health And Manage Obesity

ABSTRACT

Monitoring and rewarding of physical activity are carried out by: (1) receiving a measurement of a physical activity from a sensor; (2) processing the measurement of the physical activity to derive a valid extent of the physical activity; and (3) controlling an entertainment device based on the valid extent of the physical activity.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims the benefit of U.S. Provisional Application Ser.No. 61/467,744 filed on Mar. 25, 2011, the disclosure of which isincorporated herein by reference in its entirety.

FIELD OF THE INVENTION

The invention generally relates to the monitoring of exercise or otherforms of physical activity and, more particularly, to the monitoring andrewarding of physical activity.

BACKGROUND

The detrimental effects of childhood obesity on the health and lifespanof an individual coupled with its far reaching grip on today's youthhave caused concern that approaches the level of a nationwide pandemic.A sedentary lifestyle can be a significant contributor to childhoodobesity. On the other hand, exercise can help children control theirweight, and can help to reduce the risk of illnesses such as high bloodpressure, heart disease, and sleep problems. However, many children failto exercise because they excessively spend time doing stationaryactivities such as playing video games or watching television.

It is against this background that a need arose to develop theapparatus, system, and method described herein.

SUMMARY

One aspect of the invention relates to a non-transitorycomputer-readable storage medium. In one embodiment, the storage mediumincludes executable instructions to: (1) receive a measurement of aphysical activity from a sensor; (2) process the measurement of thephysical activity to derive a valid extent of the physical activity; and(3) control an entertainment device based on the valid extent of thephysical activity.

Another aspect of the invention relates to a system for monitoring andrewarding physical activity. In one embodiment, the system includes: (1)a processing unit; and (2) a memory connected to the processing unit andincluding executable instructions to: (a) receive an identification ofvalid instances of a physical activity by a user; and (b) control accessof the user to an entertainment device based on the valid instances ofthe physical activity.

Other aspects and embodiments of the invention are also contemplated.The foregoing summary and the following detailed description are notmeant to restrict the invention to any particular embodiment but aremerely meant to describe some embodiments of the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

For a better understanding of the nature and objects of some embodimentsof the invention, reference should be made to the following detaileddescription taken in conjunction with the accompanying drawings.

FIG. 1: Block diagram of a system for monitoring and rewardingchildren's physical activity, in accordance with one embodiment of theinvention.

FIG. 2: Block diagram of hardware and software components of a physicalactivity monitor, in accordance with one embodiment of the invention.

FIG. 3: Applying step-matching to an acceleration signal, according toan embodiment of the invention.

FIG. 4: Histogram similarity approach, according to an embodiment of theinvention.

FIG. 5: A computer configured in accordance with one embodiment of theinvention.

FIG. 6: A gait cycle divided into four time intervals, according to anembodiment of the invention.

DETAILED DESCRIPTION 1. General Description of System

FIG. 1 shows a block diagram of a system for monitoring and rewardingchildren's physical activity, in accordance with one embodiment of theinvention. The system allows children to use a set of entertainmentappliances 1 through N, such as a television set, a video game console,an audio equipment, or another electronic entertainment device,depending on the amount of exercise or other physical activity performedby the children. In one embodiment, the system operates in asubstantially automatic manner. By providing positive reinforcement, thesystem can provide the children with a sense of achievement, whileaddressing concern by parents about the children's lack of physicalactivity.

As shown in FIG. 1, the system includes three main, interconnectedcomponents: (1) a physical activity monitor (or module) 1; (2) a mainhost 2 including a computer interface; and (3) a power controller (orcontroller module) 3. The power controller 3 is connected to poweroutlets 6, which supply power to the entertainment appliances 1 throughN, and the power controller 3 can activate and deactivate theentertainment appliances 1 through N by adjusting the amount of powersupplied by the power outlets 6. In some embodiments, and depending onthe amount of physical activity performed by the children, the powercontroller 3 can selectively activate (or selectively deactivate) asubset of the entertainment appliances 1 through N, while a remainingsubset of the entertainment appliances 1 through N is deactivated (oractivated). As shown in FIG. 1, the system also includes a web server 4,which provides functionalities for kids, parents, and caregivers, suchas sign-up, reporting, behavior monitoring, diagnostic, and otherfunctionalities. In some embodiments, physical activity monitors 1 canbe directly or indirectly connected to entertainment appliances such astelevisions. In such embodiments, the power controller 3 and the mainhost 2 can be incorporated in an entertainment appliance. Moreover, datauploads and other communications with the web server 4 can be directlyperformed by the entertainment appliance itself.

FIG. 2 shows a block diagram of hardware (a) and software components (b)of the physical activity monitor 1, in accordance with one embodiment ofthe invention. The physical activity monitor 1 can measure and processdata associated with a physical activity, such as acceleration data inone or more spatial dimensions as a function of time.

As shown in FIG. 2, the physical activity monitor 1 includes a processor9 (e.g., a central processing unit (CPU)), which is connected to astorage medium 10 and a set of sensors 7. The set of sensors 7 caninclude a single sensor or a combination of sensors of the same type ordifferent types, which measure a physical activity such as walking,running, load carrying, or jumping. The set of sensors 7 can be includedin the physical activity monitor 1, or can be separate from andconnected to the physical activity monitor 1. The physical activitymonitor 1 can be physically attached to, or carried by, a child (oranother performer of a physical activity), and can be connected to themain host 2 through a wireless or a wired connection of a communicationunit 8. The physical activity monitor 1 can include a pedometer, forexample. Alternatively or in addition, the physical activity monitor 1can include other types of sensors, such as a heart-rate monitor orpressure sensors. The physical activity monitor 1 also can be in theform of a software application on a smart phone that includes anaccelerometer. For example, the application can incorporate computercode to detect physical activity based on data measured by anaccelerometer built in or connected to the smart phone. The applicationcan be developed for a particular operating system of the smart phone,such as Android.

In one embodiment, the physical activity monitor 1 can identify orrecognize the type of exercise being carried out by a child. Forexample, the physical activity monitor 1 can be configured todistinguish between different activities such as walking uphill ordownhill, walking on a level surface, running, heavy load carrying, andso forth. The physical activity monitor 1 also can be configured todistinguish between different types of environments in which a physicalactivity is performed, such as the type surface including walking ongrass, uneven ground, gravel, sand, carpet, and so forth. Therecognition of the type of activity and the type of environment can becarried out in accordance with supervised techniques or unsupervisedtechniques. For example, certain aspects of an unsupervised techniquefor exercise recognition is set forth in U.S. Provisional ApplicationSer. No. 61/448,602 filed on Mar. 2, 2011, the disclosure of which isincorporated herein by reference in its entirety. Such function can becarried out by a module 13 stored or residing in the storage medium 10.Alternatively or in addition, either of, or both, the main host 2 andthe web server 4 can perform such function by processing data measuredby the physical activity monitor 1.

In one embodiment, the physical activity monitor 1 can calculate orderive parameters indicative of an extent of a physical activity, suchas distance traveled, duration of exercise, intensity of exercise (e.g.,pace of a walk or run), and calories or energy burned as a result ofexercise. The calculation of such parameters can be based on the type ofexercise that is performed, the type of environment in which theexercise is performed, or both. For example, the physical activitymonitor 1 can use the notion of MET (Metabolic Equivalent of Task) toderive the number of calories burned by a child. The calculation ofexercise parameters can be carried out by a module 14 stored or residingin the storage medium 10. Alternatively or in addition, either of, orboth, the main host 2 and the web server 4 can perform such function byprocessing data measured by the physical activity monitor 1.

In one embodiment, the physical activity monitor 1 can performprocessing of measurements of physical activity by the set of sensors 7to reduce or minimize the vulnerability of the system to false positivesand cheating. The processing of measurements to mitigate against falsepositives and cheating can be carried out by modules 11 and 12 stored orresiding in the storage medium 10. Alternatively or in addition, eitherof, or both, the main host 2 and the web server 4 can perform suchfunction by processing data measured and provided by the physicalactivity monitor 1.

In one embodiment, the physical activity monitor 1 can validate, ordetermine a valid extent of, measurements of a physical activity made bythe set of sensors 7. A measurement of a physical activity can beinvalid (or have a valid extent of zero). For example, if some form ofcheating has occurred, such as when a first child attaches the physicalactivity monitor 1 to a second child who performs an exercise, ameasurement of the exercise can be deemed invalid. In another example, ameasurement of a physical activity, such as a step count, can be deemedinvalid because other types of physical activities, such as shaking of apedometer, can be mistakenly interpreted by the pedometer as steps.Also, a measurement of a physical activity can be substantially valid(or have a positive valid extent). For example, the physical activitymonitor 1, through processing of pressure data or acceleration data, canvalidate or determine a valid (accurate) extent of a step countassociated with the pressure data or acceleration data resulting from awalking or running activity.

Referring back to FIG. 1, the main host 2 can reside in, or correspondto, a parent's computer. When a child activates the physical activitymonitor 1, a software component of the main host 2 can retrieve datafrom the physical activity monitor 1 and store that data in the parent'scomputer. The data from the physical activity monitor 1 can betransmitted to either of, or both, the main host 2 (through a homenetwork via Wi-Fi or LAN, or using protocols such as Bluetooth, Zigbee,or other similar protocols) and the web server 4 through the Internet(such as via cellular communications). In this manner, a database of themain host 2 and a database of the web server 4 can be updated with thelatest information regarding the child's daily activity. In oneembodiment, these databases can be synchronized even if, for example,cellular coverage is not available or the child is not in the vicinityof the main host 2.

Based on a valid extent of a physical activity, the main host 2 canissue a command to the power controller 3, which activates (ordeactivates) one or more of the entertainment appliances 1 through N inaccordance with the command. In this manner, the main host 2, incombination with the power controller 3, can control operation of theentertainment appliances 1 through N as a reward for physical activity,while mitigating against false positives and cheating. In oneembodiment, the power controller 3 can be integrated into a homeautomation system that controls the power outlets 6 in a wirelessfashion or via underlying power lines. Based on a physical activitylevel of a child, the main host 2 can allot a time budget for one ormore of the power outlets 6 corresponding to specific appliances. Inthis embodiment, the power controller 3 can deactivate a correspondingappliance when the time budget expires, so that the child is forced toleave the appliance. In this manner, the main host 2, in combinationwith the power controller 3, can control a child's access to thefunctionality of the corresponding appliance. To do so, the main host 2can issue a command to the power controller 3, and the power controllercan transmit a radiofrequency (RF) signal to activate (or deactivate)one or more of the power outlets 6.

Alternatively or in addition, a controller module can be included as asoftware application that interacts with entertainment applicationsresiding in a child's computer 5, such as video games. If a physicalactivity by the child has a sufficient valid extent, the child can berewarded with a stronger avatar for local or web-based games on thechild's computer 5, or can be rewarded, based on the child's exerciserecords, with other types of visual feedback incentives throughinteraction with the child's computer 5. These additional types ofincentives, in addition to control of access to the entertainmentappliances 1 through N, can further persuade the child to engage inhealthy physical activity.

In one embodiment, a mapping between a valid extent of a physicalactivity by a child and an allotted time budget (or amount of anothertype of incentive described above) can be adjusted or otherwiseconfigured. For example, the time budget can linearly increase as afunction of the valid extent of the physical activity by the child.Alternatively or in addition, the time budget can increase as a stepfunction. For example, the child can receive no time budget until thevalid extent of the physical activity by the child exceeds or reachessome minimum value. Allocation of the time budget can be up to a maximumvalue that a child can receive per period of time, such as per day. Inone embodiment, the mapping between the valid extent of the physicalactivity by the child and the time budget (amount of another type ofincentive described above) can vary across different types of appliancesand across different applications, such as video games. In oneembodiment, the main host 2 has a recommended mode that calculates atime budget based on characteristics such as age, sex, height, andweight. It is contemplated that adults also can benefit from the systemin addition to children.

2. Determining Valid Extent of Physical Activity with a Second Type ofSensor

This section and the following sections describe the processing ofmeasurements of a physical activity to mitigate against false positivesand cheating. As previously described, in one embodiment, a measurementof a physical activity, such as a step count for walking or running, canbe deemed invalid because other types of physical activities, such asshaking of a pedometer, can be mistakenly interpreted by the pedometeras steps.

In one embodiment, a first sensor can be a pedometer attached to aperson's clothing, placed in the person's pocket, or embedded in theperson's shoe. The first sensor can provide a first measurement of aphysical activity such as walking or running. In some instances, asignificant fraction of detected steps can be a result of falsepositives stemming from intentional or unintentional movements along avertical axis. To combat this issue, a second sensor of a different typefrom the first sensor can provide a second measurement of the physicalactivity. The first sensor and the second sensor can be included in thephysical activity monitor 1, or can be separate sensors that communicatewith the physical activity monitor 1.

In one embodiment, the second sensor can include a first pressure sensorlocated in a first area of a shoe insole corresponding to a heel area ofa foot, and a second pressure sensor located in a second area of theshoe insole corresponding to a ball area of the foot. As indicated byFIG. 6, in each gait cycle for walking, there is a time interval when aconsiderable amount of pressure is applied to the heel area, namely aheel strike. Also, there is a time interval when a considerable amountof pressure is applied to the ball of the foot, namely right before atoe off. Therefore, checking an output of the pressure sensors at theright time (or checking a pattern or time variation of the output versusan expected gait cycle) can be used to verify that a recent detectedstep is indeed an actual step, rather than some other type of physicalactivity. It is worth noting that similar strategies can be applied forrunning (with a potentially different pattern) to decrease the number offalse positives.

Alternatively or in addition, the second sensor can include additionalpressure sensors. For example, the second sensor can include three,four, or more pressure sensors located in the heel area, the ball area,and other areas of the foot.

For the example set forth in FIG. 6, a pressure threshold for the firstpressure sensor located in the heel area of the shoe insole can beconfigured as a value T1=(weight of person (kg)·g (N/Kg))/(50 (cm²))N/cm². If a pressure detected by the first pressure sensor exceeds orreaches T1, then a heel strike (corresponding to a “1” in the leftmostbit of the two-bit pairs shown in FIG. 6) is detected. Otherwise a “0”is detected by the first pressure sensor. Similarly, a pressurethreshold for the second pressure sensor located in the ball area of theshoe insole can be configured as a value T2=(weight of person (kg)×g(N/Kg))/(50 (cm²)) N/cm². If the pressure detected by the secondpressure sensor exceeds or reaches T2, then a ball strike (correspondingto a “1” in the rightmost bit of the two-bit pairs shown in FIG. 6) isdetected. Otherwise a “0” is detected by the second pressure sensor. Thevalue of 50 cm² for T1 and T2 represents a typical value of the heelarea or the ball area, and can be adjusted or otherwise configured for aparticular person.

The data measured by the pressure sensors in the shoe insole can bevaluable when the physical activity monitor 1 uses a typical pedometerto measure a physical activity. In this case, to prevent false positives(e.g., as a result of the pedometer being intentionally orunintentionally shaken), recent pressure data is checked to see if aconsiderable amount of pressure has been applied to at least one of theheel area and the ball area. In one embodiment, the physical activitymonitor 1 validates, or determines a valid extent of, data measured bythe pedometer for a physical activity based on data measured by thepressure sensors for the same physical activity. Alternatively or inaddition, either of, or both, the main host 2 and the web server 4 canperform such function by processing data measured by the physicalactivity monitor 1.

To determine a valid extent of a first measurement by the first sensor(such as a pedometer), data from the first pressure sensor and thesecond pressure sensor are checked for at least a subset of possible (orcandidate) steps detected by the pedometer. For example, if output ofthe pedometer is active (e.g., a possible step is detected by thepedometer), then recent pressure data measured by the first pressuresensor (heel area) and the second pressure sensor (ball area) arechecked for a “01” pattern, a “11” pattern, or a “10” pattern (as shownin FIG. 6). In one embodiment, the recent pressure data is pressure datameasured in a time period of one second or less prior to the detectionof the possible step by the pedometer. Note that a time interval betweena heel strike and a ball strike is typically less than 0.5 seconds, evenfor a slow walk. The detection of one of these patterns (or a sequenceof these patterns) validates the detected step by the pedometer, as thestep detected by the pedometer correlates to a recent application ofsufficient pressure to at least one of the pressure sensors. In oneembodiment, the step detected by the pedometer can be deemed valid basedon the detection of any of the “01”, “11”, or “10” patterns in therecent time period.

In one embodiment, each possible step detected by the first sensor (suchas a pedometer) can be checked against data from the second sensor (suchas first and second pressure sensors). Alternatively, a subset ofpossible steps detected by the first sensor can be checked against datafrom the second sensor. The number of detected steps can be corrected orotherwise adjusted based on a percentage of steps that were detectedcorrectly by the first sensor. For example, if 90% of the detected stepsby the first sensor are validated based on the second sensor, then avalid extent of the step data can be 90% of the step data measured bythe first sensor. An entertainment appliance, such as an electronicentertainment device, can then be controlled based on this valid extentof the step data.

3. Determining Valid Extent of Physical Activity with a PhysicalActivity Template

As previously described, in one embodiment, processing by the physicalactivity monitor 1 can determine a valid (accurate) extent of a physicalactivity, such as walking or running. For example, the physical activitymonitor 1 can determine a valid step count based on acceleration data.This processing can be facilitated by determining a physical activitytemplate, and by applying the physical activity template to measuredacceleration data to count a number of instances of the activity thathave occurred, such as a number of steps for a walking or runningactivity.

In one embodiment, an accelerometer can be included in a sensor thatmeasures a physical activity such as walking or running. Theaccelerometer can be included in the physical activity monitor 1. Atemplate matching approach can reliably measure a number of steps takenby a person. The template matching approach is based on a template,which represents a typical step cycle. More generally, a template canidentify or represent an aspect of a physical activity of a particulartype, such as a walking step, a running step, and so forth.

In one embodiment, an acceleration data signal can be divided intomultiple data blocks having a particular duration in time, such as datablocks of about 10 seconds. FIG. 3( a) depicts a 10-second data blockmeasured from a left foot along the x-axis, containing six step cycles.A low-pass filter with a cutoff frequency of about 20 Hz is applied tothe signal to facilitate further processing, as shown in FIG. 3( b).

The template matching approach can then examine whether any physicalactivity template already exists, such as residing in the storage medium10. The physical activity template can be derived from measurements ofthe same type of physical activity during a training period, which canbe a time duration of at least about 10 seconds, such as a time durationof about 1 minute. Alternatively or in addition, a first step cycle(e.g., a time duration at the beginning of the measured data signal,such as an initial 10 second period of the measured data signal) can beextracted as a temporary template. Another portion of the measured datasignal also can be extracted as the temporary template. In oneembodiment, the template can be derived by the physical activity monitor1. Alternatively or in addition, the template can be derived by eitherof, or both, the main host 2 and the web server 4.

An instance of a physical activity (or another event) can be detected ina measured data signal when there is a sufficient degree of similaritybetween the measured data signal and the template. In one embodiment,the template is slid across the entire or a portion of the data signal,and a normalized cross-correlation is calculated between the templateand the measured data signal (see FIG. 3( c)). The normalizedcross-correlation indicates the similarity between the template and themeasured data signal, as set forth in

$\begin{matrix}{{{R_{N}\lbrack k\rbrack} = {\frac{\langle{X,Y}\rangle}{\sqrt{{X} \cdot {Y}}} = \frac{R_{XY}(k)}{\sqrt{{R_{XX}(0)} \cdot {R_{YY}(0)}}}}},} & (1)\end{matrix}$

In equation (1), X represents the template, Y represents the measureddata signal, k is an index representing a time lag, <X, Y> is the innerproduct of X and Y, ∥X∥ is the norm of X, ∥Y∥ is the norm of Y,R_(XY)(k) is the cross-correlation of X and Y for arbitrary k, R_(XX)(0)is the auto-correlation of X at zero lag, and R_(YY)(0) is theauto-correlation of Y at zero lag. In one embodiment, thecross-correlation can be derived by the physical activity monitor 1.Alternatively or in addition, the cross-correlation can be derived byeither of, or both, the main host 2 and the web server 4.

In one embodiment, a maximum value for the normalized cross-correlationis 1 for absolute identity, which allows a uniform threshold to be setfor all data despite varying amplitudes. Peaks in the normalizedcross-correlation in FIG. 3( c) can indicate significant similaritybetween the template and the data signal segment, and thus theoccurrence of an event (e.g., a step). An interval during which thecross-correlation exceeds or reaches a threshold T (e.g., 0.4) can bedefined as a peak searching interval. Such intervals are marked with asolid line in FIG. 3( c) and with dashed lines in FIG. 3( d). Localmaxima falling within the peak searching intervals in the filteredsignal are marked as fiducial points of steps, and denoted by asterisksin FIG. 3( d). Using the template matching approach, initial positivepeaks of steps, which occur when feet lift off the ground, are detected,and the number of steps is correspondingly counted.

In one embodiment, a physical activity template can be derived based onan average of multiple step cycles, which can be a more representativetemplate than a temporary template. For example, in FIG. 3, six stepcycles can be detected based on locating the peaks in the data block.These six step cycles can be aligned based on the location of theirpeaks and averaged together to derive a new template, which can beapplied for further processing of subsequent data blocks. Alternativelyor in addition, multiple step cycles in a longer time duration, such asabout 1 minute, can be detected based on locating peaks in an initialdata block of a shorter time duration. These multiple step cycles can bealigned based on the location of their peaks and averaged together toderive a new template, which can be applied for further processing.

Step cycles can be detected based on various techniques, such as (a)finding zeros of a signal; (b) computing the signal's energy; or (c)using the concept of salience used in speech processing. In oneembodiment, given that a signal from a sensor, such as an accelerometer,is mixed with noise, the third technique can yield a higher accuracy.The salience of a given data sample can be defined as the length of thelongest interval over which the sample is a maximum. The term saliencevector denotes a signal containing the salience of each sample in anoriginal, input signal. As a result of feet striking the ground whilewalking, a start of each walking cycle typically has a large salience.Therefore, cycles can be detected by locating such distinct points.

In one embodiment, the number of steps in a data block, such as a blockof acceleration data for walking, can be derived as follows. First, asalience of each sample of the accelerometer data in an input signal rcan be found, and a corresponding salience vector, s, can be created.Then, the vector u=(r·s)/max(s) is computed, where “·” represents anelement-wise multiplication. This transformation makes the peaks of rmore pronounced and attenuates other elements of r. Then, elements in ubeyond or reaching a certain threshold are extracted as potential cycleindices. Then, a difference d between these results is computed. Anyresults differing by a single sample can be discarded. Based on anoriginal signal assumption, an average (or mean) of the difference d cancorrespond to be an average (or mean) of a cycle length. Then, thedifference d is normalized around its mean, and the indices which fallwithin the threshold are extracted. These are the cycle starting andending points. The number of steps in the data block is then derived as:(number of extracted indices −1).

If a template is already present, peaks can be detected using thetechniques stated above. Before a next data block is processed using thesame template, a determination can be made as to whether the templatewill be updated. A step signal may change dynamically with time;accordingly, the template may not accurately represent a current stepsignal. In one embodiment, if major peaks in a normalizedcross-correlation are lower than 0.55 (or another threshold), a newtemplate can be derived using step cycles in a current data block.Otherwise, peak detection is carried out in the current data block usingthe existing template.

4. Determining Valid Extent of Physical Activity Through UserAuthentication

As previously described, in one embodiment, a measurement of a physicalactivity by a first sensor, such as a step count for walking or running,can be deemed invalid because a detected identity of a performer of thephysical activity (as measured by the first sensor) does not correspondto an identity associated with, or assigned to, the first sensor. In oneembodiment, an unique identifier can be assigned to a given physicalactivity monitor 1 (which can include the first sensor) to associate thephysical activity monitor 1 with a given person. If exercise performedby a different person is measured by the physical activity monitor 1,then the system can detect the exercise as cheating.

To detect this type of cheating, the system can determine whether thephysical activity monitor 1 is being carried by the person to whom thephysical activity monitor 1 is assigned, or by a different person. Inone embodiment, such determination is carried out through a histogramcomparison to derive a similarity score.

A first histogram, namely a template histogram, can be derived thatidentifies or represents characteristics of a first instance of aphysical activity of a particular type, such as walking or running,where it is known that the first instance of the physical activity isperformed by the person to whom the physical activity monitor 1 isassigned. The template histogram can be derived during a trainingperiod. In one embodiment, the template histogram can be derived by thephysical activity monitor 1. Alternatively or in addition, the templatehistogram can be determined by either of, or both, the main host 2 andthe web server 4.

A second histogram, namely a measured histogram to be validated, can bederived that identifies or represents characteristics of a secondinstance of the same type of physical activity, where it is desired todetermine whether the second instance of the physical activity isperformed by the person to whom the physical activity monitor 1 isassigned, or by a different person. In one embodiment, the measuredhistogram can be derived by the physical activity monitor 1.Alternatively or in addition, the measured histogram can be determinedby either of, or both, the main host 2 and the web server 4.

Based on a comparison of the template histogram to the measuredhistogram, a valid extent of measurements of the second instance of thephysical activity can be derived. In particular, the system candetermine whether the second instance of the physical activity isperformed by the person to whom the physical activity monitor 1 isassigned (if the template histogram is sufficiently similar to themeasured histogram), or by a different person. The comparison of thetemplate histogram to the measured histogram can occur during averification period separate from the training period.

Certain factors can affect the accuracy of a histogram similaritydetermination for user authentication. First, each histogram can includea number of bins (or resolution) that can correspond to the number ofdifferent recognizable outputs that a sensor (such as an accelerometer)can provide. Second, each histogram can include a number of observations(data points) that can correspond to a sampling rate of the sensor timesa duration of the physical activity, such as each step.

In one embodiment, the template histogram is derived by measuring afirst instance of a physical activity of a known type (such as walkingor running) and performed by a known person to whom the physicalactivity monitor 1 is assigned. A duration of the first instance of thephysical activity can be long enough to include at least several cyclesof the physical activity, such as multiple steps or strides. Forexample, the duration of the first instance of the physical activity canbe at least about ten seconds, and can be about one minute or more, suchas up to about five minutes, about ten minutes, or more.

In one embodiment, the measured histogram is determined by measuring asecond instance of the same type of physical activity. A duration of thesecond instance of the physical activity can be long enough to includeat least several cycles of the physical activity, such as multiple stepsor strides. For example, the duration of the second instance of thephysical activity can be at least about ten seconds, and can be aboutone minute or more, such as up to about five minutes, about ten minutes,or more. The duration of the second instance of the physical activitycan be the same as, or different from, the duration of the firstinstance of the physical activity.

In one embodiment, an output range of a sensor, such as anaccelerometer, is divided into n intervals (typically 100 bins forsampling rates no more than about 100 Hz). Each interval can correspondto a bin of at least one of the template histogram and the measuredhistogram. With regard to the template histogram, each data point fromthe first instance of the physical activity can be included in thetemplate histogram. For a sampling rate of about 100 Hz, all data pointscan be taken into consideration, namely the number of observations isequal to the number of data points.

Various metrics can be used to determine a similarity between thetemplate histogram and the measured histogram. In one embodiment, anabsolute distance metric can be used to derive a similarity scorebetween these histograms. The template histogram and the measuredhistogram can be normalized prior to their comparison, and an absolutedistance can be derived as set forth in equation (2):

$\begin{matrix}{{{dist}\left( {x,y} \right)} = {\sum\limits_{i = 1}^{n}{{x_{i} - y_{i}}}}} & (2)\end{matrix}$

Here, x_(i) is the probability of a data point residing in bin i of thenormalized template histogram, and y_(i) is the probability of a datapoint residing in bin i of the normalized measured histogram. In oneembodiment, this distance value represents a similarity score betweentwo acceleration signals. This metric is both computationallystreamlined and effective at measuring similarity between histograms forauthenticating the identity of a person performing various types ofphysical activities.

If a physical activity is performed by the same person to whom thephysical activity monitor 1 is assigned, the distance value is typicallysmaller than a resulting distance value when the physical activity isperformed by an impostor. A combined acceleration signal, namely anacceleration signal that combines accelerations along multiple axes(e.g., all three axes), can yield further improvements in authenticatingthe identity of a performer of the physical activity. In one embodiment,operations involved in comparing two gait samples using the histogramsimilarity approach are visualized in FIG. 4.

FIG. 5 illustrates a computer 800 configured in accordance with oneembodiment of the invention. The computer 800 includes a CPU 802connected to a bus 806. Input/output (I/O) devices 804 are alsoconnected to the bus 806, and can include a keyboard, mouse, display,and the like. A computer program for determining a valid extent ofmeasurements as described above is stored in a memory 808, which is alsoconnected to the bus 806. Computer programs providing functionalitycorresponding to at least one of the physical activity controller 1, themain host 2, the power controller 3, and the web server 4 can also bestored in the memory 808.

An embodiment of the invention relates to a non-transitorycomputer-readable storage medium having computer code thereon forperforming various computer-implemented operations. The term“computer-readable storage medium” is used herein to include any mediumthat is capable of storing or encoding a sequence of instructions orcomputer codes for performing the operations described herein. The mediaand computer code may be those specially designed and constructed forthe purposes of the invention, or they may be of the kind well known andavailable to those having skill in the computer software arts. Examplesof computer-readable storage media include, but are not limited to:magnetic media such as hard disks, floppy disks, and magnetic tape;optical media such as CD-ROMs and holographic devices; magneto-opticalmedia such as floptical disks; and hardware devices that are speciallyconfigured to store and execute program code, such asapplication-specific integrated circuits (“ASICs”), programmable logicdevices (“PLDs”), and ROM and RAM devices. Examples of computer codeinclude machine code, such as produced by a compiler, and filescontaining higher-level code that are executed by a computer using aninterpreter or a compiler. For example, an embodiment of the inventionmay be implemented using Java, C++, or other object-oriented programminglanguage and development tools. Additional examples of computer codeinclude encrypted code and compressed code. Moreover, an embodiment ofthe invention may be downloaded as a computer program product, which maybe transferred from a remote computer (e.g., a server computer) to arequesting computer (e.g., a client computer or a different servercomputer) via a transmission channel. Another embodiment of theinvention may be implemented in hardwired circuitry in place of, or incombination with, machine-executable software instructions.

While the invention has been described with reference to the specificembodiments thereof, it should be understood by those skilled in the artthat various changes may be made and equivalents may be substitutedwithout departing from the true spirit and scope of the invention asdefined by the appended claims. In addition, many modifications may bemade to adapt a particular situation, material, composition of matter,method, operation or operations, to the objective, spirit and scope ofthe invention. All such modifications are intended to be within thescope of the claims appended hereto. In particular, while certainmethods may have been described with reference to particular operationsperformed in a particular order, it will be understood that theseoperations may be combined, sub-divided, or re-ordered to form anequivalent method without departing from the teachings of the invention.Accordingly, unless specifically indicated herein, the order andgrouping of the operations is not a limitation of the invention.

What is claimed is:
 1. A non-transitory computer-readable storagemedium, comprising executable instructions to: receive a firstmeasurement of a physical activity from a first sensor; process thefirst measurement of the physical activity to derive a valid extent ofthe physical activity; and control an entertainment device based on thevalid extent of the physical activity.
 2. The non-transitorycomputer-readable storage medium of claim 1, further comprisingexecutable instructions to receive a second measurement of the physicalactivity from a second sensor that is different from the first sensor,and wherein the executable instructions to process the first measurementof the physical activity include executable instructions to derive thevalid extent of the physical activity based on the second measurement ofthe physical activity.
 3. The non-transitory computer-readable storagemedium of claim 2, wherein the first measurement is a measurement ofacceleration, and the second measurement is a measurement of pressure.4. The non-transitory computer-readable storage medium of claim 3,wherein the executable instructions to derive the valid extent of thephysical activity include executable instructions to correlate themeasurement of acceleration with sufficient pressure applied to at leastone area of a foot relative to a threshold pressure value.
 5. Thenon-transitory computer-readable storage medium of claim 1, wherein theexecutable instructions to process the first measurement of the physicalactivity include executable instructions to: derive a physical activitytemplate; and apply the physical activity template to the firstmeasurement to derive the valid extent of the physical activity.
 6. Thenon-transitory computer-readable storage medium of claim 5, wherein theexecutable instructions to apply the physical activity template includeexecutable instructions to: derive a cross-correlation between thephysical activity template and the first measurement; and detect anumber of peaks in the cross-correlation.
 7. The non-transitorycomputer-readable storage medium of claim 1, further comprisingexecutable instructions to receive a second measurement of the physicalactivity from the first sensor, and wherein the executable instructionsto process the first measurement of the physical activity includeexecutable instructions to authenticate an identity of a performer ofthe physical activity based on the second measurement of the physicalactivity.
 8. The non-transitory computer-readable storage medium ofclaim 7, wherein the first measurement and the second measurement aremeasurements of acceleration.
 9. The non-transitory computer-readablestorage medium of claim 7, wherein the executable instructions toauthenticate the identity of the performer of the physical activityinclude executable instructions to: derive a measured histogram and atemplate histogram corresponding to the first measurement and the secondmeasurement, respectively; and derive a similarity score between themeasured histogram and the template histogram.
 10. The non-transitorycomputer-readable storage medium of claim 1, wherein the executableinstructions to control the entertainment device include executableinstructions to activate the entertainment device based on the validextent of the physical activity.
 11. The non-transitorycomputer-readable storage medium of claim 1, wherein the executableinstructions to control the entertainment device include executableinstructions to allot a time budget for the entertainment device basedon the valid extent of the physical activity.
 12. A system formonitoring and rewarding physical activity, comprising: a processingunit; and a memory connected to the processing unit and includingexecutable instructions to: receive an identification of valid instancesof a physical activity by a user; and control access of the user to anentertainment device based on the valid instances of the physicalactivity.
 13. The system of claim 12, wherein the memory furtherincludes executable instructions to: receive a measurement from a sensorthat is applied to the user; and process the measurement to identify thevalid instances of the physical activity.
 14. The system of claim 13,wherein the measurement is indicative of multiple, candidate instancesof the physical activity, and the executable instructions to process themeasurement include executable instructions to identify a subset of thecandidate instances as the valid instances of the physical activity. 15.The system of claim 14, wherein the executable instructions to processthe measurement include executable instructions to compare themeasurement with a physical activity template to identify the validinstances of the physical activity.
 16. The system of claim 14, whereinthe measurement is a first measurement, the sensor is a first sensor,the memory further includes executable instructions to receive a secondmeasurement from a second sensor that is applied to the user, and theexecutable instructions to process the first measurement includeexecutable instructions to identify the subset of the candidateinstances as correlated with the second measurement.
 17. The system ofclaim 13, wherein the executable instructions to process the measurementinclude executable instructions to authenticate an identity of the userto whom the sensor is assigned.
 18. The system of claim 17, wherein theexecutable instructions to authenticate the identity of the user includeexecutable instructions to: derive a measured histogram corresponding tothe measurement; and derive a similarity score between the measuredhistogram and a template histogram assigned to the user.
 19. The systemof claim 12, wherein the executable instructions to control access tothe entertainment device include executable instructions to activate theentertainment device based on the valid instances of the physicalactivity.
 20. The system of claim 12, wherein the executableinstructions to control access to the entertainment device includeexecutable instructions to allot a time budget for the entertainmentdevice based on the valid instances of the physical activity.